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Research on the High-Quality Development of College Students' Education in the Context of Big Data

Author(s)

Xiaoqin Wu*

Affiliation(s)

Shandong Technology and Business University, Yantai, Shandong, China *Corresponding Author.

Abstract

This research aims to explore the high-quality development of college education in the context of big data, addressing the challenges and opportunities brought by technological advancements. Using a qualitative approach, the study examines how technologies such as artificial intelligence, data mining, and virtual reality can be integrated into teaching practices to improve educational outcomes. Key results reveal that big data has the potential to personalize learning by analyzing students' behaviors, learning preferences, and academic needs, allowing for tailored educational experiences that improve both engagement and understanding. Additionally, the research demonstrates that data-driven evaluation systems can offer more precise insights into student performance, helping to balance knowledge acquisition with the assessment of critical thinking, moral values, and practical skills. The study also highlights the importance of online platforms in supporting continuous teacher development, ensuring educators stay updated with modern teaching methods and technologies. In conclusion, fully leveraging big data technologies can significantly enhance the quality of college education, contributing to students' academic and personal growth.

Keywords

Big Data; College Education; Data Mining; Personalized Learning; Artificial Intelligence

References

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